1. Field of the Invention
The invention belongs to the field of food detection technology. In particular, it relates to a method for measuring the amount of oat flour addition in compound flours and noodles.
2. Description of the Related Art
Oat is the sixth most important cereal crop in the world, which is rich in variety and widely planted in China. Oat has high value in medical applications, health protection and cosmetic applications, for example, it can used in the prevention of vascular sclerosis and colon carcinoma, and improvement of immunity. Currently, there are many researches on oats at home and aboard, and there are a large varieties of oat products in the market. Oat flour plays an important role in breakfast cereals and flour products containing oat flour as an ingredient, where the most common ones are oat flours and noodles blended with oat. With addition of oats in the food, it brings more nutritious components to the food.
Although oat is widely used in flour products, there are also some major issues. Driven by economic interests, there is food adulteration on the market, especially adulteration of raw materials. For example, adding wheat flour to oat flour in order to reduce raw material costs, or adding a small amount of oats in oat products but charging more with less are common problems in food products. These food adulteration issues not only affect customer health and their economic interests, but also have a negative influence on the whole food industry chain. However, current research on detection of adulteration in flour products and monitoring of the flour production process is very rare. There is no accurate detection method for resolving this issue, thus making it impossible to establish a standard for quality control of cereal products. This is a large oversight in cereal food quality control management. Therefore, to establish a cereal food quality monitoring method is an imminent task. On one hand, this method will facilitate promotion and popularization of new and improved products, improve food quality, and enhance the overall level of cereal products; on the other hand, this method will provide a good database and a reference point for monitoring cereal adulteration in the food industry.
Ning Wang and his colleagues (2014) have researched the method for determining the amount of wheat flour adulterated in oat flour using a near infrared spectroscopy (NIR), balanced incomplete block design (BIBD) and least square analysis method. Although using NIR, an indirect analysis technology, to monitor cereal adulteration has advantages such as high speed, non-damage and non-pollution, there are many disadvantages as well. Firstly, a large amount of representative samples with known chemical data are needed to build a database and set up a quantitative model. Secondly, the conditions used to establish the model, such as particle size, moisture content, color, purity, test conditions, pretreatment method, can affect the accuracy of the detection. Furthermore, limited by the detection technology, different instruments with different models can result in instrumental errors. With continuous change of instrument models and changes in food samples, the quantitative model cannot be used universally, thus resulting in the increased cost of re-establishing models. Lastly, the accuracy of corresponding chemical values also needs to be validated.